Super typhoon Haiyan makes landfall
Super typhoon Haiyan
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Lake Maggiore - Italy, 3-6 April 2000


de Wasseige Carlos*, Lissens Gil**, Vancutsem Christelle*, Veroustraete Frank** and Defourny Pierre*
* Department of Environmental Sciences - Université catholique de Louvain
Croix du Sud, 2 bte 16 B-1348 Louvain-la-Neuve
** Vito - Flemish Institute for Technological Research
Boeretang, 200 B-2400 Mol

Paper (pdf file, 65 k)

High temporal resolution satellites, such as VEGETATION provide multiple images of the same site over short periods of time. Time series constituted of these individual images are characterised by a lack of signal consistency since measured radiances generally result from various cloudiness, atmospheric and geometric conditions. To reduce the related noise, various compositing techniques are available.

The pre-launch phase went into a systematic investigation of the main issues related to the temporal synthesis production using a one-year time series simulated for the VEGETATION sensor spectral and geometric configuration. The aim of that investigation was to test globally the sensitivity of the compositing process to different factors that perturb the signal, i.e. the sun-target-sensor geometry, the atmospheric conditions and the surface anisotropy. Perturbing factors have been ranked according to their impact on the sensor signal. This sensitivity analysis highlighted the large effect of the viewing angle as opposed to atmosphere variability with regard to day-to-day variations. However, the perturbing factors were always manifested as a coupled effect on the sensor signal. The analysis of the one-year simulated time series showed three nested scales of variation. A five-day cycle related to the viewing angle and due to the wide swath of the sensor. A 26-day cycle corresponding to the satellite orbit revisit time, and the sun annual cycle changing according to latitude. The conclusions drawn from the pre-launch phase of the VEGETATION programme have resulted in a proposal for two new image compositing strategies.

The approach pursued in the pre-launch phase was repeated using actual VEGETATION data in the post-launch phase. Three decades of global daily VGT-P were used. Decade 1 from 11/06/98 to 20/06/98, decade 2 from 21/07/98 to 31/07/98 and decade 3 from 11/10/98 to 20/10/98 were selected. A sampling approach based on the global dataset of VGT-P segments was designed with 50 x 50km chips to asses the performances of the existing compositing strategies for the various sun-target-sensor geometries and the different surfaces of the main terrestrial biomes. The spatial and temporal variability of the signal was first analysed for the various chips with regard to the simulation results.

The current compositing technique for VEGETATION data (VGT-S10 product) shows radiometric artefacts in the reflective bands that may cause a significant noise for subsequent retrievals of surface parameters. The performances of various compositing strategies are assessed as well for the reflective bands as for the NDVI composites. Dedicated indicators and statistical analysis are computed to provide quantitative results by zone and by band.

An innovative strategy such as the Median Composite of FUzzy Multispectral Estimate (MC-FUME) has been developed as well, to produce composites with reflectance values independent of the observation/illumination geometry at the time of measurement. Potential improvements were first tested based on selected NOAA AVHRR multitemporal time series. The results obtained using actual VEGETATION data are compared to the current MVC-NDVI approach and to other documented alternatives. A discussion of the results will provide suggestions for possible improvements in the VEGETATION processing chain compositing algorithms.